“The Thin Edge of the Wedge”: Accurately Predicting Shot Outcomes in Tennis using Style and Context Priors



The aim of this paper is to discover patterns of player movement and ball striking (short-and longterm shots, and shot combinations) in tennis using HawkEye data which are indicative of changing the probability of winning a point. This is a challenging task because: i) behavior can be unpredictable, ii) the environment is dynamic and the output state-space is large and iii) examples of specific interactions between agents may be limited or non-existent (player A may not have interacted with player B). However, by using a dictionary of discriminative patterns of player behavior, we can form a representation of a player’s style, which is interpretable latent factors that allows us to personalize interactions between players based on the match context (opponent, matchscore). This approach allows us to perform superior point predictions, and to understand how points are won by systematically creating and exploiting spatiotemporal dominance.

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